My dataset is about clients in arrears and contain the two following columns:
cured which takes value 1 when the client cured and 0 otherwise, and
self_cured which takes value 1 when client cured by themselves and 0 when they cured after being contacted. The dataset includes other behaviour and application variables as well.
I'm interested in studying the likelihood of a client in arrears to self cure.
As you can see, there's a conditionality in my data: the
self_cured variable is only relevant when the client cured (so, has a 1 in
To account for this, I thought maybe I could do what I call a "two phase regression", that would look like this:
reg 1: cured ~ application_vars + behaviour_vars + u
which will give the probability of cure aka the people that "will" cure
reg 2: self_cured ~ application_vars + behaviour_vars + s
reg 1 would be a logistic regression run with the entire dataset and
reg 2 just with the ones that were found cured from the first regression.
My question is, is there a name for this kind of thing? Do you have any sugestion about this?